Enhancing Energy-Resource Allocation in Cloud Environments: A Hybrid Approach Integrating Whale Optimization Algorithm

Enhancing Energy-Resource Allocation in Cloud Environments: A Hybrid Approach Integrating Whale Optimization Algorithm | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Enhancing Energy-Resource Allocation in Cloud Environments: A Hybrid Approach Integrating Whale Optimization Algorithm Shanky Goyal This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5887770/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The ability to access, modify, and configure data online via the web is provided by cloud computing. The term "cloud" describes an internet network that may be accessed remotely and from any location at any time. Given that more money is invested in real, physical infrastructure than in cloud technologies, cloud computing is unquestionably an innovation. The topic of power consumption by cloud infrastructure is the focus of this paper. Algorithms and methods that can lower energy usage and schedule resources are required for servers to function effectively. Another important component of cloud computing is load balancing, which allows for the balanced distribution of load among several servers in order to meet customers' increasing demands. The current study employed a variety of optimization strategies, including Particle Swarm Optimization (PSO), Cat Swarm Optimization (CSO), BAT, Cuckoo Search Algorithm (CSA) optimization algorithm, Whale optimization algorithm (WOA) and Hybrid WOABAT or load balancing, energy economy, and improved resource scheduling. The Whale optimization algorithm performed better than other algorithms in terms of response time, energy consumption, execution time, and throughput when tested with 7 and 8 servers. Dynamic resource allocation Load balancing Energy Efficiency Performance Optimization Power consumption Scalability Management Cloud Computing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5887770","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":406917177,"identity":"d9ad3b1e-c428-4aeb-bf79-31f498997b66","order_by":0,"name":"Shanky Goyal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAElEQVRIie2PsUrEMByHf6XQOhS6JlNfIV1OhON8lZSALhG3m+oREDr1AXr4FC7imCPQW8S5g4NB6OTQSRQcbI9ztD03wXxD+PMnH/kCOBx/EQJ4CvDjUHHdfW/5IQottd1Uv1HAmuzFRId0JTfXrV0XCNEIbub5VYLQPMPe/6ywp/o4vS3ge2XLjay3qYrOGLKHEYXwGbW94oeSmwtV97+QQFaMhFXnbzslwGVnTgYlfh1X0MgZHcKiI86Np3IOMvEKa+SSVo/EJ5Hmm7LWaUFapifC7mi5nIvTrRLde75K4lhY+zEWNuAFROxHg6A/9YTQ84nFflpNX3Y4HI5/xxegilTEpGbXDwAAAABJRU5ErkJggg==","orcid":"","institution":"Chandigarh Engineering College, Chandigarh Group of Collegs, Jhanjeri, Mohali - 140307, Punjab, India","correspondingAuthor":true,"prefix":"","firstName":"Shanky","middleName":"","lastName":"Goyal","suffix":""}],"badges":[],"createdAt":"2025-01-23 11:08:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5887770/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5887770/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98109881,"identity":"d63bf58f-8188-457a-848e-d054033aaa19","added_by":"auto","created_at":"2025-12-13 02:08:40","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":510579,"visible":true,"origin":"","legend":"","description":"","filename":"AHybridApproachIntegratingWhaleOptimizationAlgorithm.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5887770/v1_covered_691a2d66-958e-4199-b3f8-fc1afe016c0e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Enhancing Energy-Resource Allocation in Cloud Environments: A Hybrid Approach Integrating Whale Optimization Algorithm","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Dynamic resource allocation, Load balancing, Energy Efficiency, Performance Optimization, Power consumption, Scalability Management, Cloud Computing","lastPublishedDoi":"10.21203/rs.3.rs-5887770/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5887770/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The ability to access, modify, and configure data online via the web is provided by cloud computing. 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